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arabert_cross_development_task1_fold3

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bert
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@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: arabert_cross_development_task1_fold2
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # arabert_cross_development_task1_fold2
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8675
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- - Qwk: 0.0354
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- - Mse: 0.8675
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  ## Model description
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@@ -45,93 +45,83 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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- |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
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- | No log | 0.1176 | 2 | 3.8664 | -0.0149 | 3.8664 |
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- | No log | 0.2353 | 4 | 1.4090 | 0.0140 | 1.4090 |
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- | No log | 0.3529 | 6 | 0.8889 | 0.0893 | 0.8889 |
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- | No log | 0.4706 | 8 | 0.9277 | -0.1096 | 0.9277 |
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- | No log | 0.5882 | 10 | 0.9033 | -0.0849 | 0.9033 |
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- | No log | 0.7059 | 12 | 0.8647 | -0.0289 | 0.8647 |
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- | No log | 0.8235 | 14 | 0.8524 | -0.0029 | 0.8524 |
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- | No log | 0.9412 | 16 | 0.8579 | 0.0335 | 0.8579 |
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- | No log | 1.0588 | 18 | 0.8736 | 0.1138 | 0.8736 |
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- | No log | 1.1765 | 20 | 0.8546 | 0.1138 | 0.8546 |
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- | No log | 1.2941 | 22 | 0.8346 | 0.0370 | 0.8346 |
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- | No log | 1.4118 | 24 | 0.8410 | -0.0132 | 0.8410 |
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- | No log | 1.5294 | 26 | 0.8430 | 0.0871 | 0.8430 |
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- | No log | 1.6471 | 28 | 0.8280 | 0.0054 | 0.8280 |
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- | No log | 1.7647 | 30 | 0.8019 | 0.1435 | 0.8019 |
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- | No log | 1.8824 | 32 | 0.8572 | 0.0264 | 0.8572 |
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- | No log | 2.0 | 34 | 0.8264 | 0.0249 | 0.8264 |
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- | No log | 2.1176 | 36 | 0.8491 | 0.0318 | 0.8491 |
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- | No log | 2.2353 | 38 | 0.9465 | 0.0 | 0.9465 |
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- | No log | 2.3529 | 40 | 0.8744 | 0.0076 | 0.8744 |
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- | No log | 2.4706 | 42 | 0.8837 | 0.0105 | 0.8837 |
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- | No log | 2.5882 | 44 | 0.9227 | -0.0155 | 0.9227 |
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- | No log | 2.7059 | 46 | 0.8707 | -0.0166 | 0.8707 |
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- | No log | 2.8235 | 48 | 0.9522 | -0.0246 | 0.9522 |
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- | No log | 2.9412 | 50 | 1.0279 | -0.0279 | 1.0279 |
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- | No log | 3.0588 | 52 | 0.9857 | 0.0028 | 0.9857 |
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- | No log | 3.1765 | 54 | 0.8984 | 0.0071 | 0.8984 |
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- | No log | 3.2941 | 56 | 0.8708 | 0.0356 | 0.8708 |
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- | No log | 3.4118 | 58 | 0.8691 | -0.0219 | 0.8691 |
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- | No log | 3.5294 | 60 | 0.8666 | 0.0030 | 0.8666 |
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- | No log | 3.6471 | 62 | 0.8682 | -0.0216 | 0.8682 |
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- | No log | 3.7647 | 64 | 0.8560 | 0.0005 | 0.8560 |
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- | No log | 3.8824 | 66 | 0.8587 | 0.0154 | 0.8587 |
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- | No log | 4.0 | 68 | 0.8679 | 0.0575 | 0.8679 |
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- | No log | 4.1176 | 70 | 0.8602 | 0.0363 | 0.8602 |
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- | No log | 4.2353 | 72 | 0.8571 | -0.0005 | 0.8571 |
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- | No log | 4.3529 | 74 | 0.8496 | 0.0170 | 0.8496 |
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- | No log | 4.4706 | 76 | 0.8550 | 0.0797 | 0.8550 |
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- | No log | 4.5882 | 78 | 0.8587 | 0.0797 | 0.8587 |
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- | No log | 4.7059 | 80 | 0.8682 | 0.0574 | 0.8682 |
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- | No log | 4.8235 | 82 | 0.8811 | 0.0577 | 0.8811 |
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- | No log | 4.9412 | 84 | 0.8867 | 0.0577 | 0.8867 |
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- | No log | 5.0588 | 86 | 0.8858 | 0.0576 | 0.8858 |
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- | No log | 5.1765 | 88 | 0.9409 | 0.0065 | 0.9409 |
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- | No log | 5.2941 | 90 | 0.9595 | 0.0065 | 0.9595 |
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- | No log | 5.4118 | 92 | 0.9100 | 0.0576 | 0.9100 |
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- | No log | 5.5294 | 94 | 0.9069 | 0.0376 | 0.9069 |
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- | No log | 5.6471 | 96 | 0.9321 | -0.0238 | 0.9321 |
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- | No log | 5.7647 | 98 | 0.9246 | -0.0087 | 0.9246 |
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- | No log | 5.8824 | 100 | 0.9102 | 0.0061 | 0.9102 |
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- | No log | 6.0 | 102 | 0.9079 | -0.0091 | 0.9079 |
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- | No log | 6.1176 | 104 | 0.8805 | 0.0555 | 0.8805 |
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- | No log | 6.2353 | 106 | 0.8765 | 0.0356 | 0.8765 |
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- | No log | 6.3529 | 108 | 0.8826 | 0.0571 | 0.8826 |
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- | No log | 6.4706 | 110 | 0.8859 | 0.0572 | 0.8859 |
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- | No log | 6.5882 | 112 | 0.8716 | 0.0360 | 0.8716 |
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- | No log | 6.7059 | 114 | 0.8677 | 0.0363 | 0.8677 |
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- | No log | 6.8235 | 116 | 0.8685 | 0.0565 | 0.8685 |
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- | No log | 6.9412 | 118 | 0.8800 | 0.0351 | 0.8800 |
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- | No log | 7.0588 | 120 | 0.9136 | -0.0161 | 0.9136 |
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- | No log | 7.1765 | 122 | 0.9336 | 0.0076 | 0.9336 |
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- | No log | 7.2941 | 124 | 0.9134 | 0.0336 | 0.9134 |
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- | No log | 7.4118 | 126 | 0.8790 | 0.0352 | 0.8790 |
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- | No log | 7.5294 | 128 | 0.8678 | 0.0560 | 0.8678 |
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- | No log | 7.6471 | 130 | 0.8728 | 0.0731 | 0.8728 |
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- | No log | 7.7647 | 132 | 0.8699 | 0.0363 | 0.8699 |
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- | No log | 7.8824 | 134 | 0.8801 | 0.0355 | 0.8801 |
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- | No log | 8.0 | 136 | 0.9267 | 0.0082 | 0.9267 |
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- | No log | 8.1176 | 138 | 0.9701 | 0.0048 | 0.9701 |
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- | No log | 8.2353 | 140 | 1.0044 | 0.0041 | 1.0044 |
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- | No log | 8.3529 | 142 | 0.9968 | 0.0041 | 0.9968 |
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- | No log | 8.4706 | 144 | 0.9462 | -0.0196 | 0.9462 |
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- | No log | 8.5882 | 146 | 0.8966 | 0.0119 | 0.8966 |
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- | No log | 8.7059 | 148 | 0.8623 | 0.0354 | 0.8623 |
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- | No log | 8.8235 | 150 | 0.8572 | 0.1338 | 0.8572 |
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- | No log | 8.9412 | 152 | 0.8595 | 0.0913 | 0.8595 |
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- | No log | 9.0588 | 154 | 0.8634 | 0.0886 | 0.8634 |
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- | No log | 9.1765 | 156 | 0.8631 | 0.0886 | 0.8631 |
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- | No log | 9.2941 | 158 | 0.8590 | 0.1258 | 0.8590 |
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- | No log | 9.4118 | 160 | 0.8561 | 0.1130 | 0.8561 |
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- | No log | 9.5294 | 162 | 0.8560 | 0.1347 | 0.8560 |
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- | No log | 9.6471 | 164 | 0.8584 | 0.0980 | 0.8584 |
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- | No log | 9.7647 | 166 | 0.8627 | 0.0985 | 0.8627 |
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- | No log | 9.8824 | 168 | 0.8662 | 0.0354 | 0.8662 |
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- | No log | 10.0 | 170 | 0.8675 | 0.0354 | 0.8675 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_development_task1_fold3
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # arabert_cross_development_task1_fold3
14
 
15
  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5861
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+ - Qwk: 0.7634
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+ - Mse: 0.5861
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.1333 | 2 | 1.7502 | 0.1271 | 1.7502 |
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+ | No log | 0.2667 | 4 | 1.2292 | 0.1987 | 1.2292 |
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+ | No log | 0.4 | 6 | 1.3080 | 0.3555 | 1.3080 |
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+ | No log | 0.5333 | 8 | 0.9607 | 0.4976 | 0.9607 |
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+ | No log | 0.6667 | 10 | 0.8578 | 0.6328 | 0.8578 |
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+ | No log | 0.8 | 12 | 0.8243 | 0.6683 | 0.8243 |
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+ | No log | 0.9333 | 14 | 0.6736 | 0.6082 | 0.6736 |
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+ | No log | 1.0667 | 16 | 0.6841 | 0.5941 | 0.6841 |
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+ | No log | 1.2 | 18 | 0.6510 | 0.6300 | 0.6510 |
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+ | No log | 1.3333 | 20 | 0.7744 | 0.7345 | 0.7744 |
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+ | No log | 1.4667 | 22 | 0.6786 | 0.7336 | 0.6786 |
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+ | No log | 1.6 | 24 | 0.5769 | 0.6663 | 0.5769 |
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+ | No log | 1.7333 | 26 | 0.5647 | 0.6751 | 0.5647 |
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+ | No log | 1.8667 | 28 | 0.6191 | 0.7228 | 0.6191 |
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+ | No log | 2.0 | 30 | 0.6480 | 0.7149 | 0.6480 |
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+ | No log | 2.1333 | 32 | 0.5930 | 0.6377 | 0.5930 |
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+ | No log | 2.2667 | 34 | 0.5792 | 0.6840 | 0.5792 |
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+ | No log | 2.4 | 36 | 0.6399 | 0.7684 | 0.6399 |
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+ | No log | 2.5333 | 38 | 0.6099 | 0.7730 | 0.6099 |
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+ | No log | 2.6667 | 40 | 0.5513 | 0.7336 | 0.5513 |
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+ | No log | 2.8 | 42 | 0.5787 | 0.7674 | 0.5787 |
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+ | No log | 2.9333 | 44 | 0.6353 | 0.7926 | 0.6353 |
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+ | No log | 3.0667 | 46 | 0.5670 | 0.7594 | 0.5670 |
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+ | No log | 3.2 | 48 | 0.6004 | 0.7827 | 0.6004 |
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+ | No log | 3.3333 | 50 | 0.6263 | 0.7869 | 0.6263 |
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+ | No log | 3.4667 | 52 | 0.5762 | 0.7498 | 0.5762 |
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+ | No log | 3.6 | 54 | 0.5570 | 0.7472 | 0.5570 |
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+ | No log | 3.7333 | 56 | 0.6280 | 0.7790 | 0.6280 |
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+ | No log | 3.8667 | 58 | 0.6056 | 0.7764 | 0.6056 |
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+ | No log | 4.0 | 60 | 0.5239 | 0.7299 | 0.5239 |
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+ | No log | 4.1333 | 62 | 0.5192 | 0.7305 | 0.5192 |
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+ | No log | 4.2667 | 64 | 0.5703 | 0.7631 | 0.5703 |
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+ | No log | 4.4 | 66 | 0.6518 | 0.7918 | 0.6518 |
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+ | No log | 4.5333 | 68 | 0.7302 | 0.7883 | 0.7302 |
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+ | No log | 4.6667 | 70 | 0.6654 | 0.7960 | 0.6654 |
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+ | No log | 4.8 | 72 | 0.5714 | 0.7539 | 0.5714 |
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+ | No log | 4.9333 | 74 | 0.5149 | 0.7046 | 0.5149 |
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+ | No log | 5.0667 | 76 | 0.5129 | 0.6751 | 0.5129 |
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+ | No log | 5.2 | 78 | 0.5200 | 0.7257 | 0.5200 |
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+ | No log | 5.3333 | 80 | 0.5968 | 0.7701 | 0.5968 |
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+ | No log | 5.4667 | 82 | 0.6356 | 0.7899 | 0.6356 |
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+ | No log | 5.6 | 84 | 0.5976 | 0.7718 | 0.5976 |
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+ | No log | 5.7333 | 86 | 0.5510 | 0.7528 | 0.5510 |
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+ | No log | 5.8667 | 88 | 0.5499 | 0.7505 | 0.5499 |
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+ | No log | 6.0 | 90 | 0.5581 | 0.7507 | 0.5581 |
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+ | No log | 6.1333 | 92 | 0.5846 | 0.7624 | 0.5846 |
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+ | No log | 6.2667 | 94 | 0.6247 | 0.7828 | 0.6247 |
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+ | No log | 6.4 | 96 | 0.6363 | 0.7865 | 0.6363 |
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+ | No log | 6.5333 | 98 | 0.6065 | 0.7792 | 0.6065 |
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+ | No log | 6.6667 | 100 | 0.5753 | 0.7552 | 0.5753 |
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+ | No log | 6.8 | 102 | 0.5617 | 0.7438 | 0.5617 |
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+ | No log | 6.9333 | 104 | 0.5593 | 0.7415 | 0.5593 |
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+ | No log | 7.0667 | 106 | 0.5501 | 0.7410 | 0.5501 |
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+ | No log | 7.2 | 108 | 0.5736 | 0.7489 | 0.5736 |
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+ | No log | 7.3333 | 110 | 0.6235 | 0.7773 | 0.6235 |
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+ | No log | 7.4667 | 112 | 0.6392 | 0.7840 | 0.6392 |
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+ | No log | 7.6 | 114 | 0.6211 | 0.7732 | 0.6211 |
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+ | No log | 7.7333 | 116 | 0.5970 | 0.7733 | 0.5970 |
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+ | No log | 7.8667 | 118 | 0.5611 | 0.7530 | 0.5611 |
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+ | No log | 8.0 | 120 | 0.5439 | 0.7470 | 0.5439 |
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+ | No log | 8.1333 | 122 | 0.5497 | 0.7484 | 0.5497 |
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+ | No log | 8.2667 | 124 | 0.5836 | 0.7580 | 0.5836 |
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+ | No log | 8.4 | 126 | 0.6389 | 0.7749 | 0.6389 |
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+ | No log | 8.5333 | 128 | 0.6778 | 0.7817 | 0.6778 |
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+ | No log | 8.6667 | 130 | 0.6794 | 0.7790 | 0.6794 |
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+ | No log | 8.8 | 132 | 0.6575 | 0.7769 | 0.6575 |
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+ | No log | 8.9333 | 134 | 0.6182 | 0.7797 | 0.6182 |
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+ | No log | 9.0667 | 136 | 0.5921 | 0.7689 | 0.5921 |
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+ | No log | 9.2 | 138 | 0.5771 | 0.7588 | 0.5771 |
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+ | No log | 9.3333 | 140 | 0.5657 | 0.7530 | 0.5657 |
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+ | No log | 9.4667 | 142 | 0.5672 | 0.7530 | 0.5672 |
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+ | No log | 9.6 | 144 | 0.5759 | 0.7639 | 0.5759 |
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+ | No log | 9.7333 | 146 | 0.5809 | 0.7611 | 0.5809 |
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+ | No log | 9.8667 | 148 | 0.5847 | 0.7611 | 0.5847 |
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+ | No log | 10.0 | 150 | 0.5861 | 0.7634 | 0.5861 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions